
**Correlation Matrix**
pwcorr, sig star(.05)
outsheet using "correlation_matrix.csv"

**Logistic Regression/Margins/Graphing Margins**
xtset case_id year
xtset country_isonumber
duplicates report case_id year
**TABLE 1–––Hypothesis 1: Matching a legislator's education and professional experience with a committee's specific policy area significantly increases their likelihood of being appointed to that committee, with varying degrees of impact across different types of committees.**
mlogit comm_by_output_type i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term, base (3) vce (cluster case_id) rrr
margins, dydx (*) atmeans post
marginsplot, plotdimension(_predict, elabels(0 "Base" 1 "Distributive Committees" 2 "High Policy Committees" 3 "Public Goods Committees"))

*******TABLE 2–––H2a: Female legislators are more likely to be assigned to committees addressing soft issues, while their male counterparts are more likely to be assigned to committees handling hard issues**
mlogit committee_by_gender i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term womenparl, base(1) vce (cluster case_id)
margins, dydx (*) atmeans post
marginsplot, plotdimension(_predict, elabels(1 "Feminine Committees" 2 "Nuetral Committees" 3 "Masculine Committees"))

*******TABLE 3–––H2b: Compared to men, female legislators are more likely to be assigned to low-prestige committees.*****
ologit committee_by_prestige i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term womenparl, vce (cluster case_id) or
margins, dydx (*) atmeans post
marginsplot, plotdimension(_predict, elabels (1 "Low Prestige Committees" 2 "Medium Prestige Committees" 3 "High Prestige Committees"))

***FOR APPENDICES****Interaction between gender, education and professional backgrounds****

***Interaction terms for H1**
mlogit comm_by_output_type i.gender#comm_appoint_match_educ, base (3) vce (cluster case_id) rrr
mlogit comm_by_output_type i.gender#comm_appoint_match_prof_bg, base (3) vce (cluster case_id) rrr

***Interaction terms for H2a**
mlogit committee_by_gender i.gender#comm_appoint_match_educ, base (1) vce (cluster case_id) rrr
mlogit committee_by_gender i.gender#comm_appoint_match_prof_bg, base (1) vce (cluster case_id) rrr

***Interaction terms for H2b****
ologit committee_by_prestige i.gender#comm_appoint_match_educ, vce (cluster case_id) or
ologit committee_by_prestige i.gender#comm_appoint_match_prof_bg, vce (cluster case_id) or


**May 11 2024**

***ONLY Rwanda***
keep if country_isonumber ==646

**TABLE 1–––Hypothesis 1: Matching a legislator's education and professional experience with a committee's specific policy area significantly increases their likelihood of being appointed to that committee, with varying degrees of impact across different types of committees.**
mlogit comm_by_output_type i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term, base (3) vce (cluster case_id) rrr

*******TABLE 2–––H2a: Female legislators are more likely to be assigned to committees addressing soft issues, while their male counterparts are more likely to be assigned to committees handling hard issues**
mlogit committee_by_gender i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term womenparl, base(1) vce (cluster case_id)

*******TABLE 3–––H2b: Compared to men, female legislators are more likely to be assigned to low-prestige committees.*****
ologit committee_by_prestige i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term womenparl, vce (cluster case_id) or


**ONLY South Africa**
keep if country_isonumber ==710

**TABLE 1–––Hypothesis 1: Matching a legislator's education and professional experience with a committee's specific policy area significantly increases their likelihood of being appointed to that committee, with varying degrees of impact across different types of committees.**
mlogit comm_by_output_type i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term, base (3) vce (cluster case_id) rrr

*******TABLE 2–––H2a: Female legislators are more likely to be assigned to committees addressing soft issues, while their male counterparts are more likely to be assigned to committees handling hard issues**
mlogit committee_by_gender i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term womenparl, base(1) vce (cluster case_id)

*******TABLE 3–––H2b: Compared to men, female legislators are more likely to be assigned to low-prestige committees.*****
ologit committee_by_prestige i.gender comm_appoint_match_educ comm_appoint_match_prof_bg member_of_governing_party previously_served_in_comm first_term womenparl, vce (cluster case_id) or

